Triple

T3726136
Position Surface form Disambiguated ID Type / Status
Subject Ann Mara E81753 entity
Predicate relative P37 FINISHED
Object Rooney Mara E63855 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rooney Mara | Statement: [Ann Mara, relative, Rooney Mara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rooney Mara
Context triple: [Ann Mara, relative, Rooney Mara]
  • A. Rooney Mara chosen
    Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
  • B. Elizabeth "Lizette" Rooney Mara
    Elizabeth "Lizette" Rooney Mara is a member of the prominent Mara family associated with the ownership and management of the New York Giants NFL franchise.
  • C. Gillian Murphy
    Gillian Murphy is a renowned American ballet dancer and longtime principal with American Ballet Theatre, celebrated for her powerful technique and dramatic artistry.
  • D. Carmen Ejogo
    Carmen Ejogo is a British actress and singer known for her versatile film and television roles, including her acclaimed portrayal of Coretta Scott King in the historical drama "Selma."
  • E. Carey Mulligan
    Carey Mulligan is an acclaimed British actress known for her performances in films such as "An Education," "Drive," and "Promising Young Woman."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad8b1b7ef081908d2d381bbf54985a completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcaf669d48190852aaeef70265404 completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503e45050819088f51d8161b31abb completed March 14, 2026, 6:44 a.m.
Created at: March 8, 2026, 3:34 p.m.